The Application of Surface Response Methodology to the Pretreatment of WC Substrates Prior to...

The Application of Surface Response Methodologyto the Pretreatment of WC Substrates Prior

to Diamond CoatingMostafa Rezazadeh Shirdar, Abolfazl Golshan, Sudin Izman, and Danial Ghodsiyeh

(Submitted September 17, 2012; in revised form May 27, 2013; published online September 4, 2013)

High cobalt (Co) content greater than 10% in tungsten carbide is desirable because Co improves thetoughness of the cutting tool. However, the additional Co poses a huge challenge in surface preparationgiven that the Co content must be reduced to less than 1% on the substrate surface prior to applying adiamond coating. The excessive presence of Co on the substrate surface during coating suppresses diamondnucleation and causes the deterioration of diamond film adhesion. Many attempts have been made toovercome this issue, including the use of chemical etching, mechanical blasting, and heat treatment, but thesuccessful pretreatment of WC-12%Co is still very limited. In this paper, a single-step chemical pretreat-ment using a mixture of sulfuric acid and hydrogen peroxide solutions was carried out on WC-12%Co. Twoindependent variables, i.e., etching time and acid temperature, were varied in the experiments to reduce Cocontents as well as to roughen the substrate surface. The experimental plan was based on a centralcomposite design. Variance analysis was employed to verify the precision of the mathematical models andtheir relative parameters. The predicted models generated by the response surface methodology (RSM)were compared with the experimental results, and close agreement was observed. The models demonstratedthe significance of both factors, namely, acid temperature and etching time, in reducing Co contents to lessthan 1% as well as a roughening of the substrate surface within the desirable range.

Keywords analysis of variance, central composite design (CCD),cobalt content, response surface methodology (RSM),surface roughness, tungsten carbide (WC-12%Co)

1. Introduction

Cemented tungsten carbides are widely used for cuttingtools, wire drawing dies, bearings, and other wear-resistantengineering components. The life span of these components isgenerally enhanced by coating them with superhard materials,such as diamonds, through chemical vapor deposition (CVD)processes. Apart from their high hardness, a thin layer ofdiamond on the contact surface is chemically inert even at highoperating temperatures. Despite these advantages, diamondcoating procedures performed through the CVD process haveseveral limitations. Surface modification is generally requiredon the WC-Co substrate prior to the CVD diamond coatingprocess. The presence of a rich cobalt (Co) binder phase in thecemented tungsten carbide inhibits good adhesion of thediamond film to the substrate (Ref 1). This inhibition is due

to interaction of Co and the gas phase at the high temperatureduring CVD (Ref 2), which promotes the growth of anintermediate graphitic layer and ultimately results in pooradherence of diamond at the interface (Ref 3). Also, carbonmay diffuse from the deposited diamond phase into the Cobinder during the high temperature CVD coating process (Ref4). This phenomenon may form voids at the diamond/substrateinterface and, consequently, reduce the interfacial contact areaand the adhesion strength of the coated material. The harmfuleffect of Co can be minimized by eliminating the element fromthe outermost layers of Co-cemented tungsten carbide usingseveral procedures, such as mechanical blasting, thermaltreatment, selective laser treatment, and chemical etching.Apart from the above methods, an interlayer that is depositedon the top of the WC-Co substrate can also serve as a C and Codiffusion barrier during the CVD process. Each method has itsown inherent disadvantages. For instance, mechanical blastinghas a limited capability to reduce Co evenly on the substratesurface due to variation in the abrasive particles� size and ishighly dependent on the operator�s skills. As such, thesemechanical treatments are primarily followed by chemicaletching and/or application of intermediate layers. Thermaltreatment has been reported to promote WC grain growth at thesubstrate surface, increase the substrate roughness withoutforming subsurface porosity, and eliminate Co contents byevaporation. This process produces a new layer, which is oftenreferred to as the eta-phase layer (Ref 5). However, this methodis highly energy intensive, with the procedure requiring hightemperatures up to 2000 �C in the heat treatment process. Theformation of an eta-phase layer also has been said to bedetrimental to the mechanical properties of WC-Co (Ref 6). For

Mostafa Rezazadeh Shirdar, Sudin Izman, and Danial Ghodsiyeh,Department of Manufacturing and Industrial Engineering, Faculty ofMechanical Engineering, Universiti Teknologi Malaysia, 81310Skudai, Johor, Malaysia; and Abolfazl Golshan, Department ofMechanical Engineering, Faculty of Engineering, Universiti PutraMalaysia, 43400 Serdang, Selangor, Malaysia. Contact e-mail:[email protected].

JMEPEG (2014) 23:13–24 �ASM InternationalDOI: 10.1007/s11665-013-0691-z 1059-9495/$19.00

Journal of Materials Engineering and Performance Volume 23(1) January 2014—13

the interlayer technique, an additional mechanical treatment isrequired to corrugate the developed layer and increasediamond adhesion at the interlayer-diamond coating interface.Unnecessary and costly production time and procedures arespent on this technique to deposit the interlayer and, finally, tomechanically treat these layers prior to the diamond coatingprocess to obtain a meaningful result. The most recentdevelopment on Co removal is selective laser treatment. Anearly study on laser treatment was conducted by Singh et al.(Ref 7). Subsequently, Li et al. (Ref 8) proposed the use of apulsed laser to reduce the Co concentration at the WC-Cosurface. This method induced corrugation on the treatedsurface and it was claimed to promote adherent growth of theCVD diamond coatings. Recently, Barlettaa et al. (Ref 6)reported that they successfully used high power diode laserirradiation for selectively removing Co from the outermostlayer of the WC-Co surface by local melting and vaporization.Both laser irradiation methods are viewed as capital-intensivetechniques, and the present speed is considered to be relativelyslow for mass production.

Among these surface modification procedures, chemicaletching appears to be a more widely accepted method forremoving Co from the outermost layer of the WC-Co cuttingtool substrate prior to diamond coating in a mass productionenvironment. Numerous studies have been reported in whichthe Co on WC substrates is removed using acid etching. Thismodification process is carried out either under two- (2) orunder single-step pretreatment procedures. Sarangi et al. (Ref 9)investigated the effect of HCl + HNO3 + H2O, Murakami�sreagent, and a combination of Murakami�s reagent with Caro�sacid on the surface roughness and Co removal of tungstencarbide. This investigation reported that HCl + HNO3 + H2Oproduces a higher reduction in the Co contents, whileMurakami�s reagent produces a surface with a higher rough-ness. The result for Murakami with Caro�s acid agreed withresults by Polini et al. (Ref 10) and Kamiya et al. (Ref 11). Forreducing the Co contents, both research groups found that nitricacid was better than Murakami�s reagent. Sahoo and Chatto-padhyay (Ref 12) studied the effect of HNO3 + H2O,HNO3 + HCl + H2O, and HNO3 + 3HCl on the Co contentand surface roughness of WC substrate. A mixture ofHNO3 + HCl + H2O was reported as providing the bestpretreatment in terms of reducing the Co content, rougheningthe surface, and improving the diamond coating performance.Tang et al. (Ref 13) and Ilias et al. (Ref 14) carried out hightemperature etching with nitric acid to produce a betterdiamond coating. Jackson et al. (Ref 15) studied the perfor-mance of CVD diamond-coated tungsten carbide burs aftertreating the substrates using a two-step chemical pretreatmentprocedure that involves Murakami�s reagent etching followedby acid (96 wt.% H2SO4 + 30 wt.% H2O2) etching. Removingthe Co surface layer was reported to result in much betteradhesion of the diamond.

Svensson (Ref 16) also studied the effect of an electrolyticprocess combined with a single-step pretreatment for reducingCo binder on the WC surface. A US Patent (Ref 16) presented asingle electrolytic etching treatment process on WC-5.5%Co ina mixture containing concentrated sulfuric and phosphoricacids with a water content of <50% at a temperature range of25-60 �C. The proposed method claimed to remove Co binderon the WC substrate without the formation of pores between thetungsten carbide grains, and consequently deep penetration ofCo removal can be avoided.

A review of the literature indicates that a topic that has notbeen adequately investigated is the effect of etching parametersat high temperatures on WC with Co contents greater than 10%.In addition, most of the past studies have presented experi-mental results based on the effect of one factor (parameter) at atime (OFAT). As such, the relationship of each parameter andtheir interaction effect on Co removal and the etched substrate�ssurface roughness could not be established in the form of amathematical model. In the present manuscript, this investiga-tion is focused on the removal of Co from the WC-12%Cosurface at various temperatures. As described earlier, Coremoval studies on 12% Co-cemented tungsten carbide arevery rarely reported. The literature also shows that optimizationtechniques, such as response surface methodology (RSM), areseldom used to model the effectiveness of the surfacepreparation. The main aim of this study is to establish anempirical model that can predict the optimum etching conditionfor removing the Co outermost layer as well as for rougheningthe WC substrate surface.

2. Experimental Details

2.1 Substrate Material Preparation

The substrate used in this study was tungsten carbide (WC-12%Co). In the initial stage of preparation, the tungsten carbidewas cut using a precision cutter to 12 mm in diameter and4 mm in thickness. The contaminants and dust were thenremoved using a steam cleaner. The upper surface of thesubstrate with no burr was chosen as the etched surface to beanalyzed. The bottom surface of the substrate was markedusing a permanent marker pen. This was performed todifferentiate from the substrate surface under study.

2.2 Sand Blasting

The blasting process was carried out using a blast weartester (BWT) before the acid etching pretreatment. Thesubstrate surfaces were blasted with silicon carbide (SiC180#) abrasive for an estimated time of 10 s for each part toenhance the surface roughness and facilitate later Co removalby the chemical pretreatment.

2.3 Single-Step Etching

Chemical etching was carried out after the sand blastingprocess. Removing the Co content and roughening the substrateare considered the main reasons for using this process.Cleaning and drying of the substrate were conducted after theblasting process using a steam cleaner (Harnisch + Rieth D-S100A) to insure all of the chemicals and dirt had been removedso that additional chemical reactions would not occur. Thesteam nozzle must be held at a distance of 1-2 mm.

After removing the contaminants, the substrate was etchedusing acid etching with H2SO4 (95%) + H2O2 (30%). A heaterwas used during the chemical pretreatment to change the acidtemperature. This heater also had an ultrasonic bath machinewith a 55 kHz frequency. The beaker containing the chemicaletching reagent and the substrate was placed inside theultrasonic bath machine, which was filled with water. Thesubstrates were rinsed in deionized water, cleaned, and thendried at each stage of the pretreatment. The surface roughness of

14—Volume 23(1) January 2014 Journal of Materials Engineering and Performance

the substrate samples was measured using a portable surfaceroughness tester (Mitutoyo Surftest SJ-301). A total of 4measurements were taken and the average of the Ry values wascalculated. The surface morphologies of the substrate sampleswere analyzed using a field emission scanning electron micro-scope (FESEM), while the surface compositions (Co content)were characterized by energy dispersive x-ray analysis (EDX).

3. Experimental Design

This research is an experimental investigation of the effectof a single-step pretreatment on roughening the substratesurface and reducing the Co content on the surface. There weretwo factors considered to be in this study: the acid temperatureand the etching time. The low, middle, and high levels of thesetwo parameters are given in Table 1. Design Expert softwarewas employed for the statistical design of the experiments anddata analysis. The surface roughness and Co content wereinvestigated using the standard RSM design known as thecentral composite design (CCD). The factorial portion is a fullfactorial design, with all of the combinations of the factors atthree levels, and the star points are located on the faces of thecube in the design, with two replicates. The star pointscorrespond to an a value of 1, and this design is commonlyreferred to as a face-centered CCD. The center points are pointswith all levels set to coded level 0; the midpoint of each factorrange is repeated three times. Eighteen performance tests wereperformed. Table 2 shows the experimental plan for two factorsand three levels.

4. Response Surface Methodology

When the response under study is influenced by severalvariables, RSM provides useful mathematical and statisticaltechniques for modeling and analysis of engineering problems.Because the characteristics of the relationship between theresponse and the independent variables are often unknown, thefirst step in RSM is to find a suitable approximation for the truefunctional relationship between the response ‘‘y’’ and a set ofindependent variables x1; x2 . . . xnf g (Ref 17). A second-ordermodel is employed when the response function is non-linear orunknown:

! ¼ b0 þXk

i¼1biXi þ

Xk

i¼1biiX

2i

Xk

ii�1

Xk

j

bij � Xi � Xj þ � � � þ e

ðEq 1Þ

where i enumerates the linear coefficients, j enumerates thequadratic coefficients, b represents the regression coefficients,k is the number of experimental factors, and e is the randomerror. The wide use of this second-order model is due notonly to its flexibility in describing a wide variety of func-tional forms but also to the remarkable ability to solve realresponse surface problems with this model (Ref 18). Analysisof variance (ANOVA) is also used to estimate the suitabilityof the regression model. To this end, the ratio of the variance,due to the effect of each model factor and the variance result-ing from the error terms, termed the F ratio, was calculatedusing the ANOVA procedure. The F value is used to deter-mine the significance of the model using the variance of allof the terms at an appropriate level, a.

The significance of the individual model coefficients istested by optimizing the model by adding or deleting coeffi-cients through backward elimination, forward addition, orstepwise elimination/addition/exchange (Ref 19). The proba-bility of significance, known as the P value, is determined inthe first step. The effect of the independent variable issignificant if the P value is equal to or less than the selecteda-level, and the insignificant variables are those with P valuesgreater than the selected a-level (Ref 20). Note that the effectsof the interactions between pairs of variables can be significanteven though the effect of one variable is not individually

Table 1 Pretreatment factors and their levels

Parameters Symbol

Levels

Low (21)Centerpoint (0) High (1)

Acid temperature, �C A 1 2 3Etching time, min B 25 35 45

Table 2 Experimental plan

Sampleno. Run

Acidtemperature, �C

Etchingtime, min

1 11 25 12 6 25 13 9 45 14 3 45 15 2 25 36 4 25 37 7 45 38 5 45 39 1 35 210 10 35 211 8 35 212 12 25 213 13 45 214 14 35 115 15 35 316 16 35 217 17 35 218 18 35 2

Fig. 1 FESEM micrographs of the incoming substrate after blasting


significant; hence, the insignificant individual variables are notconsidered in backward elimination.

5. Results and Discussion

The results and discussion are categorized into threesegments that are relevant to the aforementioned experimentalphases. These three segments include the experimental results,the response surface analysis results, and validation of theexperimental results.

5.1 Experimental Results

A blasting process was performed after the cutting processfor surface treatments, such as surface strengthening, surfacemodification, surface smoothing or roughening, and surface

clearing. Figure 1 shows FESEM micrographs of one substrateafter blasting. This figure reveals that the whole surface isdamaged and rough. The WC grains are still bound together byCo as no WC grains can be clearly observed, even thoughportions of the WC grains are beginning to be exposed.

Figures 2 and 3 show the measurement results of the surfaceroughness and Co content, respectively, after the blastingprocess. The average surface roughness Ry after blasting is3.73 lm, while the average Co content is 11.26(%). In thisexperiment, the sand blasting process has the least significanteffect on reducing the percentage of the Co content. During thisprocess, the Co still adheres to the substrate and is not removedby the bombardment of the sand blasting particles.

As mentioned above, the Caro�s acid etching experimentinvolved 18 trials, and the responses of the surface roughnessand the Co content were measured. All of the experimentalresults are presented in Table 3. As a result of the acid etching,

Fig. 2 Surface roughness after blasting

Fig. 3 Co content after blasting


the surface roughness slightly increased and the Co contentsignificantly decreased. The ratio of the surface roughness foreach substrate is taken, which is the average surface roughnessafter Caro�s acid etching divided by the average surfaceroughness value after the blasting process. These results werefurther analyzed with the Design Expert software. The ratio wastaken because the initial surface roughness value after blastingvaried slightly. By taking the ratio, the effect of surfaceroughness variations after treating the substrate with Caro�s acidetching was eliminated. Figure 4 shows the FESEM micro-graphs after the substrates were acid etched at different levels ofacid temperature and etching time. This result shows that theCo was removed after the acid etching process. The EDAXresults shown in Fig. 5 confirm the percentage of surface Coand the WC content.

5.2 Response Surface Analysis Results

The model summary statistics for surface roughness and Cocontent are given in Tables 4 and 5, respectively. Tables 4 and5 reveal that the best models are quadratic models. Thus,quadratic models are used for proper analysis.

Table 3 Experimental results

Sampleno. Run

Acidtemperature,

�C

Etchingtime,min

Surfaceroughness

ratio

Cocontent,

%

1 11 25 1 0.92 1.272 6 25 1 0.90 1.293 9 45 1 1.13 1.564 3 45 1 1.24 1.475 2 25 3 1.07 1.136 4 25 3 1.03 1.067 7 45 3 1.26 0.678 5 45 3 1.30 0.599 1 35 2 1.17 1.0110 10 35 2 1.23 1.0611 8 35 2 1.16 1.0312 12 25 2 1.01 1.1713 13 45 2 1.21 1.1014 14 35 1 1.05 1.3815 15 35 3 1.18 0.8916 16 35 2 1.17 1.1517 17 35 2 1.18 1.0918 18 35 2 1.14 1.11

Fig. 4 FESEM micrograph after acid etching: (a) acid temperature 25 �C, etching time 1 min; (b) acid temperature 35 �C, etching time 2 min;and (c) acid temperature 45 �C, etching time 3 min


Fig. 5 EDAX spectra of the substrate surface: (a) substrate after acid etching, acid temperature 25 �C, etching time 1 min; (b) substrate afteracid etching, acid temperature 35 �C, etching time 2 min; and (c) substrate after acid etching, acid temperature 45 �C, etching time 3 min

Table 4 Model summary statistics for surface roughness

Source SD R2 Adj. R2 Pred. R2 PRESS

Linear 0.048 0.8495 0.8280 0.7614 0.051Interaction 0.049 0.8542 0.8205 0.7184 0.060Quadratic 0.034 0.9399 0.9126 0.8253 0.038 Suggested

Table 5 Model summary statistics for Co content

Source SD R2 Adj. R2 Pred. R2 PRESS

Linear 0.14 0.7195 0.6794 0.4564 0.54Interaction 0.052 0.9644 0.9562 0.9286 0.071Quadratic 0.038 0.9841 0.9768 0.9529 0.047 Suggested


An ANOVA test was applied to provide an optimumcombination of the pretreatment parameters and consequentlythe surface roughness and Co content. The response surfacequadratic model resulting from the ANOVA for the surfaceroughness is presented in Table 6. The significant model termsare those with a value less than 0.050 for ‘‘Prob>F,’’ whichare shown in Table 6. Therefore, A, B, and A2 are thesignificant terms of the model. An improved model can beobtained by omitting those model terms with a value greaterthan 0.1. Table 7 shows the ANOVA table that results fromthe reduced quadratic model for the surface roughnessobtained by implementing the backward elimination procedureto automatically reduce the number of terms. A model F valueof 43.27 reveals that the model is still significant. The ‘‘Lackof fit F value’’ of 0.40 implies that the lack of fit is notsignificant relative to the pure error, and it is desirable. Thereis an 80.11% probability that a ‘‘Lack of fit F value’’ this largecould occur due to noise.

Likewise, the ANOVA table for the quadratic model for thesurface Co content is given in Table 8. The significant modelterms are A, B, and AB based on a model F value of 135.85 and

the values of ‘‘Prob>F’’ less than 0.050, as presented inTable 8. The value of R2 is 0.9841, which is very close to 1.Likewise, the predicted and adjusted R2 values are in closeagreement. The S/N ratio, which is presented with adequateprecision, is 36.898 and this indicates that the model isdesirable for navigating the design space (true when the S/Nratio is greater than 4).

The statistical models play an important role in analyzingthe surface roughness and Co content in the pretreatmentdiamond coating. The models are used for the prediction ofresults. Equations 2 and 3 are the final empirical models interms of coded factors for the surface roughness and Cocontent:

Ry ¼ 1:17þ 0:12Aþ 0:06B� 0:044A2 � 0:039B2 ðEq 2Þ

Co%¼ 1:07� 0:053A� 0:26B� 0:17ABþ 0:043A2þ 0:043B2:

ðEq 3Þ

Equations 4 and 5 are the final empirical models in terms ofactual factors for the surface roughness and Co content:

Table 6 ANOVA for the response surface quadratic model (surface roughness)

Source Sum of squares df Mean square F value P valueProb>F

Block 1.594E�004 1 1.594E�004 ÆÆÆ ÆÆÆModel 0.20 5 0.040 34.39 <0.0001 SignificantA 0.15 1 0.15 124.75 <0.0001B 0.036 1 0.036 30.67 0.0002AB 1.012E�003 1 1.012E�003 0.86 0.3729A2 5.715E�003 1 5.715E�003 4.87 0.0495B2 4.502E�003 1 4.502E�003 3.84 0.0760Residual 0.013 11 1.174E�003 ÆÆÆ ÆÆÆLack of fit 1.327E�003 3 4.423E�004 0.31 0.8209 Not significantPure error 0.012 8 1.448E�003 ÆÆÆ ÆÆÆCor total 0.021 17 ÆÆÆ ÆÆÆ

Std dev 0.034 R2 0.9399Mean 1.13 Adj R2 0.9126C.V. % 3.03 Pred R2 0.8253PRESS 0.038 Adeq precision 16.944

Table 7 ANOVA for the reduced response surface quadratic model (surface roughness)


Block 1.594E�004 1 1.594E�004 ÆÆÆ ÆÆÆModel 0.20 4 0.040 43.27 <0.0001 SignificantA 0.15 1 0.15 126.19 <0.0001B 0.036 1 0.036 31.03 0.0001A2 5.715E�003 1 5.715E�003 4.93 0.0465B2 4.502E�003 1 4.502E�003 3.88 0.0724Residual 0.014 12 1.160E�003 ÆÆÆ ÆÆÆLack of fit 2.339E�003 4 5.848E�004 0.40 0.8011 Not significantPure error 0.012 8 1.448E�003 ÆÆÆ ÆÆÆCor total 0.021 17 ÆÆÆ ÆÆÆ



Ry ¼ � 0:072126þ 0:043217Aþ 0:21781B

� 0:000444527A2 � 0:039435B2 ðEq 4Þ

Co% ¼ 1:26330� 0:000685572Aþ 0:17587B

� 0:017500ABþ 0:000434080A2 þ 0:043408B2:

ðEq 5Þ

Figures 6 and 7 show the normal probability plots for theresidual as a function of the predicted response for the surfaceroughness and Co content, respectively. It is found from Fig. 7and 8 that the residual generally falls on a straight line, and thisresult indicates that the errors are normally distributed.Therefore, the proposed models are acceptable.

The effect of the pretreatment parameters on the surfaceroughness and Co content was also investigated using thedeveloped RSM-based mathematical model. Figures 8 and 9show the 3D graphs and contour plots of the surface roughnessand Co content, respectively, as a function of the pretreatmentparameters. From Fig. 8, increasing the acid temperature andthe etching time is observed to increase the surface roughnessof tungsten carbide, but the effect of the etching time is more

significant than that of the acid temperature. An observationfrom Fig. 9 is that, after increasing the acid temperature andtime of etching, the Co content of WC decreases, which is adesirable result.

The influence of the etching time and acid temperature in thepretreatment process is analyzed based on the developedmathematical model. Their effects on the surface roughnessratio and the Co contents are presented in Fig. 10 and 11,respectively. It is clearly seen that an increase in the etchingtime and acid temperature increases the surface roughness ofthe substrates. In contrast, a reverse phenomenon has beenobserved on the Co content, where this content is reduced whenthe etching time and acid temperature are increased. Theaggressiveness of the acid solution in attacking the tungstencarbide and Co grains is amplified at prolonged etching timesand elevated temperatures compared to conditions at roomtemperature. The results are particularly useful for researchersand engineers. A process engineer can use these plots todetermine a suitable solution in terms of particular constraintson the surface roughness ratio and Co content.

Multiple responses and factors can be optimized graphicallyby combining two or more responses into one function, referredto as an overlay plot (Ref 17). The overlay plot generallyrepresents the optimal region that satisfies the required preset

Table 8 ANOVA for the response surface quadratic model (Co content)


Block 2.364E�003 1 2.364E�003 ÆÆÆ ÆÆÆModel 0.98 5 0.20 135.85 <0.0001 SignificantA 0.028 1 0.028 19.38 0.0011B 0.69 1 0.69 477.24 <0.0001AB 0.24 1 0.24 169.04 <0.0001A2 5.449E�003 1 5.449E�003 3.76 0.0786B2 5.449E�003 1 5.449E�003 3.76 0.0786Residual 0.016 11 1.449E�003 ÆÆÆ ÆÆÆLack of fit 2.910E�003 3 9.699E�004 0.60 0.6356 Not significantPure error 0.013 8 1.629E�003 ÆÆÆ ÆÆÆCor total 1.00 17 ÆÆÆ ÆÆÆ


Fig. 6 Normal probability plot of the residuals for surfaceroughness

Fig. 7 Normal probability plot of the residuals for Co content


Fig. 8 The effect of pretreatment parameters on the surface roughness, Ry: (a) 3D graph; (b) contour plot

Fig. 9 The effect of pretreatment parameters on the Co content: (a) 3D graph; (b) contour plot

Fig. 10 Variation of the surface roughness ratio as a function of etching time during the pretreatment process for various acid temperatures


conditions. In this work, a Co content less than 1% and asurface roughness ratio within 0.9-1.3 are desirable after thepretreatment process. Figure 12 shows the overlay plot thatfulfills these requirements. The optimal region suggests thatthese outcomes can be achieved by varying the etching time tomore than 2 min with an acid temperature from 30 to 45 �C.

5.3 Validation of the Experimental Results

To certify whether the developed model is valid as aprediction tool, seven experimental runs were performed. Theresults are presented in Tables 9 and 10. For the first threeexperimental runs, the test conditions had been used in theearlier experiments. For the remaining four experimental runs,the test conditions were within the ranges of levels definedpreviously; however, the specific combinations had not beenused in the initial stage of the experiment. The surface

Fig. 11 Variation of the Co content as a function of etching time during the pretreatment process for various acid temperatures

Fig. 12 Optimal settings for reducing the Co content to less than1% at a Ry ratio within 0.9-1.3

Table 9 Confirmation tests for surface roughness

No.Temperatureof acid, �C

Etching time,min

ActualRy ratio

PredictedRy ratio Residual Error, %

1 25 1 0.92 0.91 +0.01 +1.092 35 2 1.23 1.17 +0.06 +4.883 45 3 1.30 1.27 +0.03 +2.314 30 1.5 1.12 1.06 +0.06 +5.355 30 2.5 1.13 1.12 +0.01 +0.886 40 1.5 1.20 1.18 +0.02 +1.677 40 2.5 1.21 1.24 �0.03 �2.48


roughness and Co content for the selected experiments werepredicted using the point prediction capability of the DesignExpert software with a 95% prediction interval. The predictedvalue and the associated predicted interval are based on thepreviously predicted model. The predicted value and the actualexperimental value were compared. The percentage error rangebetween the actual and predicted value for the surfaceroughness and Co content is �2.48 to 5.35 and �5.94 to0.00, respectively.

6. Conclusions

In this study, the effect of acid temperature and the time ofetching on the surface roughness and Co content of tungstencarbide (WC-12%Co) prior to diamond coating was studied.Statistical models were built using RSM to overcome thelimitation of classical methods. These models were successfullyemployed to obtain the optimum process conditions, and theinteractions between process variables were demonstrated. Thefollowing conclusions were drawn from this study:

1. CCD was applied in this research and proven as an effec-tive tool for the prediction of surface roughness and Cocontent removal in the pretreatment of cemented tungstencarbide prior to diamond coating.

2. The reduced quadratic models developed using RSM aresuitable for prediction within the limits of the factors stud-ied.

3. The results of the ANOVA and the validation experi-ments certify that the developed mathematical models areaccurate and that there is a close agreement between thepredicted values and experimental values.

4. The influences of pretreatment parameters, such as acidtemperature and etching time, during the pretreatment pro-cess have been analyzed based on the developed mathe-matical model. A process engineer can use these results todetermine a suitable solution in terms of the particular con-straints on the surface roughness ratio and Co content.

5. In terms of future work, different types of etching solu-tions should be investigated to evaluate the effect of acidtemperature and etching time on surface roughness andCo content removal.

References

1. T. Li, Q. Lou, J. Dong, Y. Wei, and J. Liu, Modified SurfaceMorphology in Surface Ablation of Cobalt-Cemented Tungsten

Carbide with Pulsed UV Laser Radiation, Appl. Surf. Sci., 2001,172(3–4), p 331–344

2. X. Chen and J. Narayan, Effect of the Chemical Nature of Transition-Metal Substrates on Chemical-Vapor Deposition of Diamond, J. Appl.Phys., 1993, 74(6), p 4168–4173

3. K. Shibuki, M. Yagi, K. Saijo, and S. Takatsu, Adhesion Strength ofDiamond Films on Cemented Carbide Substrates, Surf. Coat. Technol.,1988, 36(1–2), p 295–302

4. R. Haubner and B. Lux, Diamond Deposition on Cutting Tools, Ceram.Int., 1996, 22(4), p 347–351

5. Jr. Gates and A. Inspektor, Diamond Coated Cutting Tools and Methodof Manufacture, Kennametal PC, US Patent No. 6524363 B2, 25 Feb2003

6. M. Barlettaa, G. Rubino, and A. Gisario, Co Removal and PhaseTransformations During High Power Diode Laser Irradiation ofCemented Carbide, Appl. Surf. Sci., 2011, 257(9), p 4239–4245

7. R.V. Singh, D.R. Gilbert, J. Fitz-Gerald, S. Harkness, and D.G. Lee,Engineered Interfaces for Adherent Diamond Coatings on LargeThermal-Expansion Coefficient Mismatched Substrates, Science, 1996,272, p 396–398

8. T. Li, Q. Lou, J. Dong, Y. Wei, J. Zhou, J. Liu, Z. Zhang, and F. Sun,Improved Adhesion of Diamond Coating on Cobalt-Cemented Tung-sten Carbide Hard Metal by Using Pulsed-UV-Laser Substrate SurfacePretreatment, Appl. Surf. Sci., 2002, 193(1–4), p 102–119

9. S.K. Sarangi, A. Chattopadhyay, and A.K. Chattopadhyay, Effect ofPretreatment, Seeding and Interlayer on Nucleation and Growth ofHFCVD Diamond Films on Cemented Carbide Tools, Int. J. Refract.Met. Hard Mater., 2008, 26(3), p 220–231

10. R. Polini, P.D. Antonio, S. Lo Casto, V.F. Ruisi, and E. Traversa,Cutting Performance and Indentation Behavior of Diamond Films onCo-Cemented Tungsten Carbide, Surf. Coat. Technol., 2000, 123(1),p 78–83

11. S. Kamiyaa, H. Takahashia, R. Polinib, P. D�Antoniob, and E. Traver-sab, Effect of WC-Co Substrate Pretreatment and Microstructure on theAdhesive Toughness of CVD Diamond, Diam. Relat. Mater., 2001,10(3–7), p 786–789

12. B. Sahoo and A.K. Chattopadhyay, On Effectiveness of Vari-ous Surface Treatments on Adhesion of HF-CVD Diamond Coatingto Tungsten Carbide Inserts, Diam. Relat. Mater., 2002, 11(9), p1660–1669

13. W. Tang, Q. Wang, S. Wang, and F. Lu, A Comparison in Performanceof Diamond Coated Cemented Carbide Cutting Tools With andWithout a Boride Interlayer, Surf. Coat. Technol., 2002, 153(2–3),p 298–303

14. S. Ilias, C. Campillo, C.F.M. Borges, and M. Moisan, DiamondCoatings Deposited on Tool Materials with a 915 MHz Scaled UpSurface-Wave-Sustained Plasma, Diam. Relat. Mater., 2000, 9(3–6),p 1120–1124

15. M.J. Jackson, L.J. Hyde, W. Ahmed, H. Sein, and R.P. Flaxman,Diamond-Coated Cutting Tools for Biomedical Applications, J. Mater.Eng. Perform., 2004, 13, p 421–430

16. R. Svensson, Etching Process, US Patent No. 5380408, 10 Jan1995

17. D.C. Montgomery, Design and Analysis of Experiments, 7th ed., Wiley,Singapore, 2009

18. R.H. Myers, D.C. Montgomery, and C.M. Anderson-Cook, ResponseSurface Methodology: Process and Product Optimization UsingDesigned Experiments, Vol 705, Wiley, New York, 2009

Table 10 Confirmation tests for Co content

No.Temperatureof acid, �C

Etchingtime, min

Actual Cocontent, %

PredictedCo content, % Residual Error, %

1 25 1 1.27 1.30 �0.03 �2.362 35 2 1.01 1.07 �0.06 �5.943 45 3 0.67 0.67 0.00 0.004 30 1.5 1.18 1.21 �0.03 �2.545 30 2.5 0.99 1.03 �0.04 �4.046 40 1.5 1.19 1.24 �0.05 �4.207 40 2.5 0.86 0.89 �0.03 �3.49


19. M.Y. Noordin, V.C. Venkatesh, S. Sharif, S. Elting, and A. Abdullah,Application of Response Surface Methodology in Describing thePerformance of Coated Carbide Tools when Turning AISI, 1045 Steel,J. Mater. Process. Technol., 2004, 145(1), p 46–58

20. B. Routara, A. Bandyopadhyay, and P. Sahoo, Roughness Modelingand Optimization in CNC End Milling Using Response SurfaceMethod: Effect of Workpiece Material Variation, Int. J. Adv. Manuf.Technol., 2009, 40, p 1166–1180


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